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The purpose of this paper is to test whether the 2007 identification of commonality in liquidity by Galariotis and Giouvris for the UK is robust to different methodological approaches; to find whether commonality is priced; and to identify how changes in trading regimes, hence liquidity provision, affect the relationship between commonality and excess returns.

The paper builds on the 2001 methodology of Huberman and Halka. In addition it extracts common factors using principal component analysis to test the effect of commonality on excess returns.

The findings of this paper confirm the presence of a systematic time‐varying component in UK spreads (under a different approach) even after controlling for well‐known spread determining variables.

The paper provides original evidence on the presence and the effect of systematic liquidity on asset pricing in the UK, showing that it is sensitive to the nature of trading regimes. It is concluded that in order‐driven regimes the effect of commonality on asset pricing is reduced, hence policy makers should consider this when deciding on trading systems

The purpose of this paper is to assess the performance of a contrarian investment strategy focusing on frequently traded large-cap US stocks. Previous criticisms that losers’ gains are not due to overreaction but due to their tendency to be thinly traded and smaller-sized firms than winners are addressed.

Portfolios based on past performance are constructed and it is examined whether contrarian returns exist. The Capital Asset Pricing Model (CAPM), Fama and French three-factor model and the Carhart’s (1997) momentum portfolio are used to test whether excess returns are feasible in a contrarian strategy.

The results show an asymmetric performance following portfolio formation. Although both, winners and losers portfolios, have gains during holding periods, losers outperform winners at all times, and with a differential of up to 29.2 per cent 36 months after portfolio formation. Furthermore, the loser and the winner portfolios’ alphas are significant, suggesting that the CAPM and the multifactor models are unable to explain return differentials between winners and losers. Our evidence supports two main conclusions. First, stock market overreaction still holds for a sample of large firms. Second, this is robust to the Fama and French’s (1993, 1996) three-factor model and Carhart’s (1997) momentum portfolio. Findings emphasize the relevance of a contrarian strategy when rebalancing investment portfolios.

Portfolio managers can improve stock returns by selling past winners and buying previous loser large-cap US stocks.

This paper is the first, to the authors’ knowledge, to examine frequently traded large-cap US stocks to avoid infrequent trading and size concerns.

The purpose of this paper is to critically review the literature on contrarian and momentum trading strategies and identify areas for future research.

Critical review and discussion of the literature.

The extant literature is dynamic and is typified by a number of open questions.

The open questions in the literature relate mainly to the driving forces of investment performance, and the role of risk and asset pricing as well as behavioral human traits. The literature is vast and therefore difficult to classify, cover and discuss.

The paper indicates the possible need for: the development of different asset pricing models and propositions that can have practical implications at a more international context.

The paper provides a critical review of the literature and identifies open issues for future research.

Behavioral finance and market microstructure studies suggest that the investor sentiment and liquidity are related. This paper aims to examine the aggregate sentiment–liquidity relationship in emerging markets (EMs) for both the sample period and crisis period. Then, it verifies this relationship, using the asymmetric sentiment.

This study uses a sample consisting of stocks listed on the SSE Shanghai composite index (348 stocks), the JKSE (118 stocks), the IPC (14 stocks), the RTS (12 stocks), the WSE (106 stocks) and FTSE/JSE Africa (76 stocks). This is for the period ranging from February, 2002 until March, 2021 (230 monthly observations). We use the panel data and apply generalized method-of-moments (GMM) of dynamic panel estimators.

The empirical analysis shows the following results: first, it demonstrates a significant relationship between the aggregate investor sentiment and the stock market liquidity for the sample period and crisis one. Second, referring to the asymmetric sentiment, we have empirically given proof that the market is significantly more liquid in times of the optimistic sentiment than it is in times of the pessimistic sentiment. Third, using panel causality tests, we document a unidirectional causality between the investor sentiment and liquidity in a direct manner through the noise traders and the irrational market makers and also a bidirectional causality in an indirect channel.

The results reported in this paper have implications for regulators and investors in EMs. Firstly, the study informs the regulators that the increases and decreases in the stock market liquidity are related to the investor sentiment, not financial shocks. We empirically evince that the traded value is higher in the crisis. Secondly, we inform insider traders and rational market makers that the persistence of increases in the trading activity in both quiet and turbulent times is associated with investor participants such as noise traders and irrational market makers.

The originality of this work lies in employing the asymmetric sentiment (optimistic/pessimistic) in order to denote the sentiment–liquidity relationship in EMs for the sample period and the 2007–2008 subprime crisis.

Based on the theoretical framework, this paper analyzes the sentiment-herding relationship in emerging stock markets (ESMs). First, it aims to examine the effect of investor sentiment on herding. Second, it seeks the direction of causality between sentiment and herding time series.

The present study applies the Exponential Generalized Auto_Regressive Conditional Heteroskedasticity (EGARCH) model to capture the volatility clustering of herding on the financial market and to investigate the role of the investor sentiment on herding behaviour. Then the vector autoregression (VAR) estimation uses the Granger causality test to determine the direction of causality between the investor sentiment and herding. This study uses a sample consisting of stocks listed on the Shanghai Composite index (SSE) (348 stocks), the Jakarta composite index (JKSE) (118 stocks), the Mexico IPC index (14 stocks), the Russian Trading System index (RTS) (12 stocks), the Warsaw stock exchange General index (WGI) (106 stocks) and the FTSE/JSE Africa all-share index (76 stocks). The sample includes 5,020 daily observations from February 1, 2002, to March 31, 2021.

The research findings show that the sentiment has a significant negative impact on the herding behaviour pointing out that the higher the investor sentiment, the lower the herding. However, the results of the present study indicate that a higher investor sentiment conducts a higher herding behaviour during market downturns. Then the outcomes suggest that during the crisis period, the direction is one-way, from the investor sentiment to the herding behaviour.

The findings may have implications for universal policies of financial regulators in EMs. We have found evidence that the Emerging investor sentiment contributes to the investor herding behaviour. Therefore, the irrational investor herding behaviour can increase the stock market volatility, and in extreme cases, it may lead to bubbles and crashes. Market regulators could implement mechanisms that can supervise the investor sentiment and predict the investor herding behaviour, so they make policies helping stabilise stock markets.

The originality of this paper lies in investigate the sentiment-herding relationship during the Surprime crisis and the Covid-19 epidemic in the EMs.